List of Articles Sisangan

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  1 - The Study of Polycyclic Aromatic Hydrocarbons (PAHs) Contamination in Sediments of Sisangan Coastal Sediments in South Caspian Sea
  Hossein bagheri Kazem Darvish Bastami Ali Hamzepour
  10.22034/jest.2019.9691
  Introduction: Polycyclic aromatic hydrocarbon (PAHs) is the most important environmental pollutants which originated from various sources. They are stable in seawater and especially in sediments and their degradation occur slowly. Sixteen numbers of this pollutant are i More

  Introduction: Polycyclic aromatic hydrocarbon (PAHs) is the most important environmental pollutants which originated from various sources. They are stable in seawater and especially in sediments and their degradation occur slowly. Sixteen numbers of this pollutant are introduced by Environmental Protection Agency (EPA) as serious carcinogen compounds. In this study, the contents of 16 PAHs compounds were determined in the sediments of Sisanagan coastal sediments (South Caspian Sea). Material and Methods: The sampling was performed by Van Veen grab from 12 sites and 4 transect of the study area. Determination of PAHs (16 components) was performed by high performance liquid chromatography (HPLC). Results: The results showed that the total concentration of PAHs varied between 94.55- 336.33 ng/g dry weight of sediments. Maximum individual concentration of PAHs was 132, 97.5 ng g-1 belonged to banzo(b) flouranthene and flouranthene and  Benzo[k]fluoranthene, dibenzo(a,h)anthracen, banzo(g,h.i)perylen, acenaphtylen, banzo(a)pyren and indino were not detected in all of the sampling sites. The total organic matters (TOM) of sampling sites were different from 1.65 to 9.95%. Conclusion: Comparison of PAHs concentrations in the studied sediments with other places in the world showed (PAHs) pollutions of studied sediments are medium to low and results also showed that PAHs pollutants in this area have both pyrogenic (Fuel) and petrogenic sources. Comparing the values obtained in this area with standard PAHs (ISQGs, NOAA) indicated contaminated sediments are not harmful effect on the creatures. Manuscript profile
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  2 - Simultaneous Usage of Double-Bounded and One and One-Half Bounded Dichotomous Choices in the Valuation of Sisangan Forest Park
  kamal Ataie Solout AhmadAlie Keikha
  10.22034/jest.2020.29652.3820
  Background and Objective: In the last decade, the valuation of public goods has been considerably taken into account. Today, countries which are more likely to consider their economic development consider the tourism industry as a necessity and since naturalism or ecoto More

  Background and Objective: In the last decade, the valuation of public goods has been considerably taken into account. Today, countries which are more likely to consider their economic development consider the tourism industry as a necessity and since naturalism or ecotourism is one of the major tourist attractions, serious attention is paid to this. The purpose of this study is an investigation of simultaneous usage of Double-Bounded Dichotomous Choices (DBDC) and one and one-half bounded Dichotomous Choices (OOHB) in determining the recreational value of Sysangan Forest Park with contingent valuation method in 2014.    Method: For this task, according to the theoretical literature of each choice, a questionnaire prepared for each choice, and necessary information gathered. Then with using Logit model and maximum likelihood method, effecting parameter on the recreation value of park estimated. Findings: According to the results; the annual number of visits, consequence or ethical oriented of visitors and monthly family income of visitors have the significant effect on willingness to pay of visitors for recreation in this park. Expected willingness to pay in DBDS choice is relatively 12.2 percentages more than the similar amount in the OOHB choice. According to the results, the recreational value estimated of Sisangan forest park, with using of DBDC and OOHB choices are respectively 14949 and 11324 million Rial in 2014. Discussion and Conclusion: Although the results of this study can not be described as a general rule, but it can be said that based on the information collected by DBDC and OOHB selections in the studied samples, the model estimated by OOHB selections to In terms of good indicators, the fit is better and the recreational value of the park is more adjusted than the model used by DBDC selection.   Manuscript profile
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  3 - Investigation of Outdoor Recreation Needs and Preferences of Visitors in Sorkhe Hesar Forest Park and Its Comparison with Sisangan Forest Park
  Saeedeh Eskandari Jafar Oladi Ghadikolaei Ali Yakhkashi
  Nowadays, assessment of the outdoor recreation demand in forest parks is very important to prepare the successful outdoor recreation plans and to schedule the facilities development in these plans. Recognition of visitor’s economic- social needs is essential to es More

  Nowadays, assessment of the outdoor recreation demand in forest parks is very important to prepare the successful outdoor recreation plans and to schedule the facilities development in these plans. Recognition of visitor’s economic- social needs is essential to estimate outdoor recreation demand, because visitor’s socio-economic conditions have the great effect on mall selection to use of it. In this study outdoor recreation demand of Sorkhe Hesar forest park in east of Tehran was evaluated by interviewing and completing of questionnaire in the spring. Obtained results of this study were compared with the results of another study done in Sisangan forest park to investigate visitor’s outdoor recreation demand changes during thirty years. Comparison of outdoor recreation demand and investigation of visitor’s needs in in-city forest parks (Sorkhe Hesar) and out-city forest parks (Sisangan) showed that visitor’s outdoor recreation demand has not changed during thirty years. In addition, visitor’s outdoor recreation demand is similar in in-city forest parks (Sorkhe Hesar) and out-city forest parks (Sisangan) (except demands that depend on visitor’s distance) and visitor’s major purpose is rest in the healthy environment and inspiration in the healthy air. Finally we suggest that outdoor recreation planners consider the visitor's demand and tendency to create and develop the forest parks. Manuscript profile
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  4 - Using canopy height model derived from UAV images to tree height estimation in Sisangan forest
  Mohammad Reza Kargar Hormoz Sohrabi
  Recent advances in unmanned aerial vehicles (UAVs) technology, as well as the development of lightweight sensors, offers a great possibility for the measurement of different tree features with relatively low costs compared to traditional methods. In this research, More

  Recent advances in unmanned aerial vehicles (UAVs) technology, as well as the development of lightweight sensors, offers a great possibility for the measurement of different tree features with relatively low costs compared to traditional methods. In this research, the precision and accuracy of tree height measurement and estimation using imagery by a low-cost UAV were studied. For this aim, 854 images with an altitude of 100 m above the ground were taken and the images were processed and dense point cloud was extracted by applying Structure from Motion (SFM) algorithm. The study was conducted in 34.79 ha of Sisangan forest park and 28 sample plots (30 × 30 m) were located in the field and tree heights were measured. Also, tree height was measured using the canopy height model. Linear regression was applied to estimate the actual tree heights based on CHM derived tree eights. The accuracy and precision of the estimates were assessed using relative bias and relative root mean square error. The differences between the field measured and CHM derived tree heights were statistically significant. Based on the results, the relative root means the square error of the height estimation of Buxus hyrcana, Carpinus betulus, Parrotia persica, and other species was 20.39, 20.39, 20.57 and 20.52 percent, respectively. The results showed that tree height measurement based on UAV images and methods that were applied in this research, is biased and the estimations are highly uncertain. Manuscript profile
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  5 - Evaluate the accuracy of Unmanned aerial vehicles (UAV) data on the survey of dieback Buxus hyrcana (Case study: Sisangan forest park-Mazandaran)
  Mohammadreza Kargar Younes Babaei Amir Eslam Bonyad
  10.30495/girs.2021.679275
  Background and ObjectiveSisangan forest park is one of the important habitats of Buxus Hyrcana in Iran. Unfortunately, the park has suffered from dieback in recent years, and many Box trees have been destroyed. Monitoring and management of this zone can be effective in More

  Background and ObjectiveSisangan forest park is one of the important habitats of Buxus Hyrcana in Iran. Unfortunately, the park has suffered from dieback in recent years, and many Box trees have been destroyed. Monitoring and management of this zone can be effective in controlling, protecting, and supporting it. However, due to the destruction of Box trees, on a large scale, it is not possible to accurately estimate the area using the available data. On the other hand, manual measurements are also very time-consuming and tedious. Therefore, a way must be found to do this process accurately and automatically. Unmanned aerial vehicles (UAV) have made this possible by using highly accurate sensors (spatial resolution). Another solution that can be used to automatically separate dieback trees from green trees is to use different classification methods. The aim of this study is to prove the ability of low-cost UAV data with conventional sensors to detect and zoning areas that have suffered Dieback. Since the cost of UAVs with multispectral sensors (red edge band and near infrared) is very high, it should be possible to reduce this cost. Since the cost of UAV with multispectral sensors (red-edge and near-infrared band) is very high, it should be possible to reduce this cost. Materials and Methods Sisangan Forest Park has located 30km to the east of Nowshahr County, Mazandaran province, at latitude 36º33′30″ to 36º35′30″ N, and longitude 51º47′ to 51º49′30″E. This park is both a tourist destination and many important plant species of the country grow in it. One of the most important of these species is the Buxus Hyrcana. But unfortunately, in recent years they have become snag due to pests and insect infestations. Multirotor UAVs have been used in this research. The camera installed on this device is capable of capturing 20 megapixel images. Imaging operations were performed on December 28, 2017, at 10:00 AM, which lasted 45 minutes. The study area was visited for field sampling and its different points were identified in terms of density of snags and preserved Buxus Hyrcana. Then, three circular pieces with a radius of 60 meters and an area of 1.13 hectares were designed in the zone and the density of snag stands and preserved Buxus Hyrcana stands were determined in these three samples. In each plot, 50 training points were recorded in the places where the Buxus Hyrcana stands were located and also 50 points were recorded in the places where the preserved Buxus Hyrcana stands, floor grass cover, and blackberry was located. In this study, in order to evaluate the accuracy of UAV images in identifying and classifying zones covered with Dieback, the smallest Dieback stands with the smallest canopy width were also recorded. Because UAV images require geometric corrections, they were first corrected geometrically and geographically. They were classified with ENVI software. According to the above explanations, 100 points were recorded in each sample plot, 75 of which were monitored for the classification process and 25 of which were used to evaluate the classification accuracy. Three monitored artificial neural network classification algorithms, maximum likelihood and minimum distance were used to classify these images. Finally, after performing each of the classification steps, a low-pass filter with a size of 3 by 3 pixels was used for smoothing the images. Kappa coefficients and overall accuracy indices were also used to evaluate the results. Results and Discussion In this number of sample plots, 579 stands were measured. Buxus Hyrcana was by far the most frequent in the zone. European hornbeam, Parrotia persica, and Oak were in the next ranks, respectively. The results showed that the artificial neural network algorithm had the best results compared to the other two algorithms. But the results of the artificial neural network also fluctuate according to the condition of the sample piece. This algorithm with an overall accuracy of 97.47% and a kappa coefficient of 0.94 had the best results in the separation and detection of the Buxus Hyrcana snags in the sample plot with the dominance of Buxus Hyrcana snags. After the artificial neural network algorithm, the maximum likelihood algorithm showed more favorable results in separating the Buxus Hyrcana snag stands. The minimum distance algorithm showed good results, but it was not as accurate as of the previous two algorithms. All three algorithms showed poorer results in separating the bases in the sample plot with the dominance of live bases in the sample than the other two sample plots. The sample piece with the predominance of live and green bases compared to the other two sample pieces has more phenomena and effects and in terms of image texture, there are many significant differences compared to the other two sample pieces. All three algorithms showed poorer results in separating the stands in the sample plot by dominance the preserved stands in the sample than the other two sample plots. The sample plot with the predominance of preserved stands compared to the other two sample plots has more phenomena and in terms of image texture compared to the other two sample plots has a lot of significant differences. In this sample plot, in addition to the presence of preserved and snag stands, grass cover and blackberry accessions can also be seen. In this study, the results of classification and detection of Buxus Hyrcana snags using an artificial neural network algorithm were much better than the maximum likelihood and minimum distance algorithms. One of the reasons for the better results of the artificial neural network algorithm is its nonlinearity and non-parametricity. But in classification by traditional algorithms such as statistical methods, they have lower accuracy because they have less flexibility. Parametric types of traditional methods, such as the maximum likelihood algorithm, due to depending on Gaussian statistics, if the data are not normal, cannot have the desired accuracy in classifying and separating classes from each other. In traditional algorithms such as maximum likelihood and minimum distance algorithms, training data play a vital role. In these methods, it is assumed that the distribution within the training samples should be normal so that if this condition cannot be met, the classification accuracy will be greatly reduced. While artificial neural network methods operate based on the characteristics and structure of the data itself. Conclusion The results of this study showed that using the data and ordinary images of a low-cost UAV, it is possible to study the condition of Dieback after the outbreak of the disease and determine its area. Despite the high cost of purchasing expensive sensors to monitor vegetation status, these methods presented in this article can be done at a much lower cost. This method can be of great help to the relevant institutions in determining the area of snag coatings. Manuscript profile